{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\burlacue\Dropbox\Corruption papper\DATAVERSE\probit-models-of-vote-for-the-incumbent.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}18 Oct 2017, 19:31:50
{txt}
{com}. 
. **** This code can be used to generate Table 2 
. * "Probit models of vote for the incumbent" in the article
. * and Tables 3 and 4 in the Online Appendix 
. 
. ***The measures for corruption should be purchased from the PRG Group. 
. *In this article, I used the monthy measures of corruption from Table 3b and 
. *calculated the annual averages:
. *forvalues i=1984/2016{c -(}
. *gen corruption`i'= _01_`i'+_02_`i'+ _03_`i'+_04_`i'+ _05_`i' + _06_`i'+ ///
> *_07_`i'+_08_`i'+ _09_`i'+_10_`i'+ _11_`i' + _12_`i'
. *{c )-}
. *drop Variable _01_1984 - _01_2017
. *reshape long corruption, i(Country) j(year)
. 
. ** These should be merged with the data. Make sure the variable is called corruption 
. 
. ** The dataset DOES NOT include a variable for corruption!!!
. 
. use "recoded_CSES_data.dta", clear
{txt}( )

{com}.  
. global controls age male income loweducation higheducation unemployed retired other partisan
{txt}
{com}. global macros growth gdp durable partyage pr pluralty mdmh p_effnv  p_maj state   east noneuro  system
{txt}
{com}. 
. global controls2 age male income loweducation higheducation unemployed retired other strengthpartisan
{txt}
{com}. global macros2 gdp durable partyage pr pluralty mdmh p_effnv  p_maj  state east noneuro  system
{txt}
{com}. 
. 
. *** Model 4 in Table 2
. 
. gen ideolcor=ideolprime*corruption
{txt}
{com}. 
. label var ideolcor "Corruption x Ideol prox"
{txt}
{com}.         
. bootstrap, clu(code study_id) rep(100): cmp (governmentvote = corruption ideolcor ideolprime $controls $macros growth), ind(4) nolr qui
{txt}(running cmp on estimation sample)

Bootstrap replications ({res}100{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
..................................................    50
..................................................   100
{res}
{txt}Mixed-process regression{col 49}Number of obs{col 67}= {res}    66,987
{txt}{col 49}Replications{col 67}= {res}       100
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   3761.77
{txt}Log likelihood = {res}-22990.124{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 80:(Replications based on {res:88} clusters in code study_id)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}   Observed{col 28}   Bootstrap{col 56}         Norm{col 69}al-based
{col 1}governmentvote{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}governmentvote {txt}{c |}
{space 4}corruption {c |}{col 16}{res}{space 2}-.0520157{col 28}{space 2} .3024637{col 39}{space 1}   -0.17{col 48}{space 3}0.863{col 56}{space 4}-.6448336{col 69}{space 3} .5408023
{txt}{space 6}ideolcor {c |}{col 16}{res}{space 2}-.1237914{col 28}{space 2}  .047897{col 39}{space 1}   -2.58{col 48}{space 3}0.010{col 56}{space 4}-.2176678{col 69}{space 3}-.0299151
{txt}{space 4}ideolprime {c |}{col 16}{res}{space 2} .2260557{col 28}{space 2} .0259494{col 39}{space 1}    8.71{col 48}{space 3}0.000{col 56}{space 4} .1751957{col 69}{space 3} .2769156
{txt}{space 11}age {c |}{col 16}{res}{space 2}-.0019386{col 28}{space 2} .0010912{col 39}{space 1}   -1.78{col 48}{space 3}0.076{col 56}{space 4}-.0040772{col 69}{space 3}    .0002
{txt}{space 10}male {c |}{col 16}{res}{space 2}-.0588595{col 28}{space 2} .0159892{col 39}{space 1}   -3.68{col 48}{space 3}0.000{col 56}{space 4}-.0901977{col 69}{space 3}-.0275213
{txt}{space 8}income {c |}{col 16}{res}{space 2} .0003978{col 28}{space 2} .0090186{col 39}{space 1}    0.04{col 48}{space 3}0.965{col 56}{space 4}-.0172785{col 69}{space 3}  .018074
{txt}{space 2}loweducation {c |}{col 16}{res}{space 2} .1203868{col 28}{space 2} .0405144{col 39}{space 1}    2.97{col 48}{space 3}0.003{col 56}{space 4}   .04098{col 69}{space 3} .1997936
{txt}{space 1}higheducation {c |}{col 16}{res}{space 2}  -.05063{col 28}{space 2} .0295351{col 39}{space 1}   -1.71{col 48}{space 3}0.086{col 56}{space 4}-.1085178{col 69}{space 3} .0072578
{txt}{space 4}unemployed {c |}{col 16}{res}{space 2} .0235272{col 28}{space 2} .0394317{col 39}{space 1}    0.60{col 48}{space 3}0.551{col 56}{space 4}-.0537574{col 69}{space 3} .1008119
{txt}{space 7}retired {c |}{col 16}{res}{space 2} .0473359{col 28}{space 2} .0288742{col 39}{space 1}    1.64{col 48}{space 3}0.101{col 56}{space 4}-.0092566{col 69}{space 3} .1039283
{txt}{space 9}other {c |}{col 16}{res}{space 2}-.0195096{col 28}{space 2} .0290892{col 39}{space 1}   -0.67{col 48}{space 3}0.502{col 56}{space 4}-.0765234{col 69}{space 3} .0375043
{txt}{space 6}partisan {c |}{col 16}{res}{space 2} 2.202782{col 28}{space 2} .0539762{col 39}{space 1}   40.81{col 48}{space 3}0.000{col 56}{space 4} 2.096991{col 69}{space 3} 2.308574
{txt}{space 8}growth {c |}{col 16}{res}{space 2} .0174641{col 28}{space 2} .0154088{col 39}{space 1}    1.13{col 48}{space 3}0.257{col 56}{space 4}-.0127367{col 69}{space 3} .0476648
{txt}{space 11}gdp {c |}{col 16}{res}{space 2} .0591593{col 28}{space 2} .0452514{col 39}{space 1}    1.31{col 48}{space 3}0.191{col 56}{space 4}-.0295318{col 69}{space 3} .1478504
{txt}{space 7}durable {c |}{col 16}{res}{space 2} .0012618{col 28}{space 2} .0018203{col 39}{space 1}    0.69{col 48}{space 3}0.488{col 56}{space 4}-.0023059{col 69}{space 3} .0048295
{txt}{space 6}partyage {c |}{col 16}{res}{space 2}-.0020569{col 28}{space 2}  .001762{col 39}{space 1}   -1.17{col 48}{space 3}0.243{col 56}{space 4}-.0055105{col 69}{space 3} .0013966
{txt}{space 12}pr {c |}{col 16}{res}{space 2}  .078967{col 28}{space 2} .1496997{col 39}{space 1}    0.53{col 48}{space 3}0.598{col 56}{space 4}-.2144389{col 69}{space 3}  .372373
{txt}{space 6}pluralty {c |}{col 16}{res}{space 2} .1684535{col 28}{space 2} .1240769{col 39}{space 1}    1.36{col 48}{space 3}0.175{col 56}{space 4}-.0747328{col 69}{space 3} .4116397
{txt}{space 10}mdmh {c |}{col 16}{res}{space 2}  .002189{col 28}{space 2} .0014722{col 39}{space 1}    1.49{col 48}{space 3}0.137{col 56}{space 4}-.0006964{col 69}{space 3} .0050744
{txt}{space 7}p_effnv {c |}{col 16}{res}{space 2}-.0479268{col 28}{space 2}  .037949{col 39}{space 1}   -1.26{col 48}{space 3}0.207{col 56}{space 4}-.1223054{col 69}{space 3} .0264518
{txt}{space 9}p_maj {c |}{col 16}{res}{space 2} .1435955{col 28}{space 2} .3572344{col 39}{space 1}    0.40{col 48}{space 3}0.688{col 56}{space 4}-.5565711{col 69}{space 3} .8437621
{txt}{space 9}state {c |}{col 16}{res}{space 2} .0437515{col 28}{space 2} .1947118{col 39}{space 1}    0.22{col 48}{space 3}0.822{col 56}{space 4}-.3378766{col 69}{space 3} .4253796
{txt}{space 10}east {c |}{col 16}{res}{space 2}-.0804048{col 28}{space 2} .1891061{col 39}{space 1}   -0.43{col 48}{space 3}0.671{col 56}{space 4}-.4510459{col 69}{space 3} .2902363
{txt}{space 7}noneuro {c |}{col 16}{res}{space 2}-.1047317{col 28}{space 2}   .15726{col 39}{space 1}   -0.67{col 48}{space 3}0.505{col 56}{space 4}-.4129557{col 69}{space 3} .2034922
{txt}{space 8}system {c |}{col 16}{res}{space 2}-.1370546{col 28}{space 2} .1172458{col 39}{space 1}   -1.17{col 48}{space 3}0.242{col 56}{space 4}-.3668522{col 69}{space 3}  .092743
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-1.188072{col 28}{space 2} .5014661{col 39}{space 1}   -2.37{col 48}{space 3}0.018{col 56}{space 4}-2.170927{col 69}{space 3}-.2052162
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store simple
{txt}
{com}. estimates save simple, replace
{res}{txt}file simple.ster saved

{com}. 
. 
. *** Model 5 in Table 2
. gen interaction=ideoldifference*ideolprime
{txt}
{com}. 
. label var interaction "Perc accuracy * Ideol proximity"
{txt}
{com}. 
. bootstrap, clu(code study_id) rep(100): cmp (governmentvote = corruption ideolcor ideolprime  ideoldifference interaction $controls $macros) (ideoldifference =  corruption $controls2 $macros2) , ind(4 1) nolr qui  iter(100)
{txt}(running cmp on estimation sample)

Bootstrap replications ({res}100{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
..................................................    50
..................................................   100
{res}
{txt}Mixed-process regression{col 49}Number of obs{col 67}= {res}    66,987
{txt}{col 49}Replications{col 67}= {res}       100
{txt}{col 49}Wald chi2({res}27{txt}){col 67}= {res}   2976.92
{txt}Log likelihood = {res}  29396.22{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Replications based on {res:88} clusters in code study_id)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}   Observed{col 30}   Bootstrap{col 58}         Norm{col 71}al-based
{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}governmentvote   {txt}{c |}
{space 6}corruption {c |}{col 18}{res}{space 2}-.1018015{col 30}{space 2} .3109212{col 41}{space 1}   -0.33{col 50}{space 3}0.743{col 58}{space 4}-.7111959{col 71}{space 3} .5075929
{txt}{space 8}ideolcor {c |}{col 18}{res}{space 2}-.0483369{col 30}{space 2} .0439347{col 41}{space 1}   -1.10{col 50}{space 3}0.271{col 58}{space 4}-.1344474{col 71}{space 3} .0377736
{txt}{space 6}ideolprime {c |}{col 18}{res}{space 2}-.1920345{col 30}{space 2}  .063682{col 41}{space 1}   -3.02{col 50}{space 3}0.003{col 58}{space 4}-.3168489{col 71}{space 3}-.0672202
{txt}{space 1}ideoldifference {c |}{col 18}{res}{space 2}-.0765753{col 30}{space 2} .2981805{col 41}{space 1}   -0.26{col 50}{space 3}0.797{col 58}{space 4}-.6609983{col 71}{space 3} .5078477
{txt}{space 5}interaction {c |}{col 18}{res}{space 2} .5039549{col 30}{space 2} .0774761{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .3521046{col 71}{space 3} .6558052
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0020307{col 30}{space 2} .0008852{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.0037656{col 71}{space 3}-.0002958
{txt}{space 12}male {c |}{col 18}{res}{space 2}-.0589328{col 30}{space 2} .0174168{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4}-.0930691{col 71}{space 3}-.0247965
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0011254{col 30}{space 2}  .009222{col 41}{space 1}    0.12{col 50}{space 3}0.903{col 58}{space 4}-.0169494{col 71}{space 3} .0192003
{txt}{space 4}loweducation {c |}{col 18}{res}{space 2} .1211492{col 30}{space 2} .0405205{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .0417306{col 71}{space 3} .2005679
{txt}{space 3}higheducation {c |}{col 18}{res}{space 2}-.0479104{col 30}{space 2} .0269208{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.1006742{col 71}{space 3} .0048533
{txt}{space 6}unemployed {c |}{col 18}{res}{space 2} .0243479{col 30}{space 2} .0391497{col 41}{space 1}    0.62{col 50}{space 3}0.534{col 58}{space 4}-.0523842{col 71}{space 3} .1010799
{txt}{space 9}retired {c |}{col 18}{res}{space 2} .0519101{col 30}{space 2} .0305495{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0079657{col 71}{space 3}  .111786
{txt}{space 11}other {c |}{col 18}{res}{space 2}-.0224255{col 30}{space 2} .0279566{col 41}{space 1}   -0.80{col 50}{space 3}0.422{col 58}{space 4}-.0772195{col 71}{space 3} .0323684
{txt}{space 8}partisan {c |}{col 18}{res}{space 2}  2.17566{col 30}{space 2} .0667815{col 41}{space 1}   32.58{col 50}{space 3}0.000{col 58}{space 4} 2.044771{col 71}{space 3} 2.306549
{txt}{space 10}growth {c |}{col 18}{res}{space 2} .0177756{col 30}{space 2}  .015372{col 41}{space 1}    1.16{col 50}{space 3}0.248{col 58}{space 4} -.012353{col 71}{space 3} .0479043
{txt}{space 13}gdp {c |}{col 18}{res}{space 2} .0584509{col 30}{space 2} .0445497{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0288649{col 71}{space 3} .1457668
{txt}{space 9}durable {c |}{col 18}{res}{space 2} .0011807{col 30}{space 2} .0022947{col 41}{space 1}    0.51{col 50}{space 3}0.607{col 58}{space 4}-.0033169{col 71}{space 3} .0056783
{txt}{space 8}partyage {c |}{col 18}{res}{space 2}-.0022008{col 30}{space 2} .0017703{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-.0056706{col 71}{space 3} .0012689
{txt}{space 14}pr {c |}{col 18}{res}{space 2}  .074277{col 30}{space 2} .1780252{col 41}{space 1}    0.42{col 50}{space 3}0.677{col 58}{space 4}-.2746461{col 71}{space 3} .4232001
{txt}{space 8}pluralty {c |}{col 18}{res}{space 2} .1692845{col 30}{space 2} .1642135{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.1525681{col 71}{space 3} .4911371
{txt}{space 12}mdmh {c |}{col 18}{res}{space 2} .0022026{col 30}{space 2} .0015527{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0008406{col 71}{space 3} .0052458
{txt}{space 9}p_effnv {c |}{col 18}{res}{space 2}-.0494255{col 30}{space 2} .0394078{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.1266634{col 71}{space 3} .0278124
{txt}{space 11}p_maj {c |}{col 18}{res}{space 2} .1147253{col 30}{space 2} .4614679{col 41}{space 1}    0.25{col 50}{space 3}0.804{col 58}{space 4}-.7897353{col 71}{space 3} 1.019186
{txt}{space 11}state {c |}{col 18}{res}{space 2} .0513702{col 30}{space 2} .1907361{col 41}{space 1}    0.27{col 50}{space 3}0.788{col 58}{space 4}-.3224658{col 71}{space 3} .4252061
{txt}{space 12}east {c |}{col 18}{res}{space 2}-.0804551{col 30}{space 2} .1999738{col 41}{space 1}   -0.40{col 50}{space 3}0.687{col 58}{space 4}-.4723965{col 71}{space 3} .3114862
{txt}{space 9}noneuro {c |}{col 18}{res}{space 2}-.1097861{col 30}{space 2} .1771472{col 41}{space 1}   -0.62{col 50}{space 3}0.535{col 58}{space 4}-.4569882{col 71}{space 3} .2374161
{txt}{space 10}system {c |}{col 18}{res}{space 2}-.1355663{col 30}{space 2} .1160786{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-.3630762{col 71}{space 3} .0919437
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -1.08674{col 30}{space 2}  .583402{col 41}{space 1}   -1.86{col 50}{space 3}0.062{col 58}{space 4}-2.230187{col 71}{space 3} .0567069
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ideoldifference  {txt}{c |}
{space 6}corruption {c |}{col 18}{res}{space 2} -.127077{col 30}{space 2} .0389743{col 41}{space 1}   -3.26{col 50}{space 3}0.001{col 58}{space 4}-.2034652{col 71}{space 3}-.0506888
{txt}{space 13}age {c |}{col 18}{res}{space 2} .0000961{col 30}{space 2}  .000077{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0000548{col 71}{space 3}  .000247
{txt}{space 12}male {c |}{col 18}{res}{space 2} .0117408{col 30}{space 2} .0014663{col 41}{space 1}    8.01{col 50}{space 3}0.000{col 58}{space 4} .0088669{col 71}{space 3} .0146148
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0078434{col 30}{space 2} .0011897{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4} .0055116{col 71}{space 3} .0101751
{txt}{space 4}loweducation {c |}{col 18}{res}{space 2}-.0138322{col 30}{space 2} .0041646{col 41}{space 1}   -3.32{col 50}{space 3}0.001{col 58}{space 4}-.0219947{col 71}{space 3}-.0056698
{txt}{space 3}higheducation {c |}{col 18}{res}{space 2} .0246189{col 30}{space 2} .0030408{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .0186591{col 71}{space 3} .0305787
{txt}{space 6}unemployed {c |}{col 18}{res}{space 2}-.0123843{col 30}{space 2} .0055696{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-.0233004{col 71}{space 3}-.0014681
{txt}{space 9}retired {c |}{col 18}{res}{space 2}-.0005073{col 30}{space 2} .0032962{col 41}{space 1}   -0.15{col 50}{space 3}0.878{col 58}{space 4}-.0069677{col 71}{space 3} .0059531
{txt}{space 11}other {c |}{col 18}{res}{space 2} .0001656{col 30}{space 2} .0038389{col 41}{space 1}    0.04{col 50}{space 3}0.966{col 58}{space 4}-.0073585{col 71}{space 3} .0076898
{txt}strengthpartisan {c |}{col 18}{res}{space 2} -.001606{col 30}{space 2}  .001487{col 41}{space 1}   -1.08{col 50}{space 3}0.280{col 58}{space 4}-.0045205{col 71}{space 3} .0013085
{txt}{space 13}gdp {c |}{col 18}{res}{space 2}-.0023685{col 30}{space 2} .0062944{col 41}{space 1}   -0.38{col 50}{space 3}0.707{col 58}{space 4}-.0147052{col 71}{space 3} .0099683
{txt}{space 9}durable {c |}{col 18}{res}{space 2}-.0003891{col 30}{space 2}  .000241{col 41}{space 1}   -1.61{col 50}{space 3}0.106{col 58}{space 4}-.0008613{col 71}{space 3} .0000832
{txt}{space 8}partyage {c |}{col 18}{res}{space 2}-.0002898{col 30}{space 2} .0002922{col 41}{space 1}   -0.99{col 50}{space 3}0.321{col 58}{space 4}-.0008625{col 71}{space 3} .0002829
{txt}{space 14}pr {c |}{col 18}{res}{space 2}-.0289863{col 30}{space 2} .0195125{col 41}{space 1}   -1.49{col 50}{space 3}0.137{col 58}{space 4}-.0672302{col 71}{space 3} .0092575
{txt}{space 8}pluralty {c |}{col 18}{res}{space 2}-.0242211{col 30}{space 2}  .018703{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-.0608784{col 71}{space 3} .0124362
{txt}{space 12}mdmh {c |}{col 18}{res}{space 2}-.0000116{col 30}{space 2} .0002573{col 41}{space 1}   -0.05{col 50}{space 3}0.964{col 58}{space 4} -.000516{col 71}{space 3} .0004928
{txt}{space 9}p_effnv {c |}{col 18}{res}{space 2}-.0119588{col 30}{space 2} .0053206{col 41}{space 1}   -2.25{col 50}{space 3}0.025{col 58}{space 4}-.0223871{col 71}{space 3}-.0015306
{txt}{space 11}p_maj {c |}{col 18}{res}{space 2}-.1323904{col 30}{space 2} .0702242{col 41}{space 1}   -1.89{col 50}{space 3}0.059{col 58}{space 4}-.2700273{col 71}{space 3} .0052466
{txt}{space 11}state {c |}{col 18}{res}{space 2} .0227717{col 30}{space 2} .0232717{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}  -.02284{col 71}{space 3} .0683834
{txt}{space 12}east {c |}{col 18}{res}{space 2}-.0036313{col 30}{space 2} .0239015{col 41}{space 1}   -0.15{col 50}{space 3}0.879{col 58}{space 4}-.0504773{col 71}{space 3} .0432148
{txt}{space 9}noneuro {c |}{col 18}{res}{space 2}-.0460927{col 30}{space 2} .0197321{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.0847668{col 71}{space 3}-.0074186
{txt}{space 10}system {c |}{col 18}{res}{space 2} .0505196{col 30}{space 2} .0235664{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .0043304{col 71}{space 3} .0967088
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .981649{col 30}{space 2} .0746879{col 41}{space 1}   13.14{col 50}{space 3}0.000{col 58}{space 4} .8352634{col 71}{space 3} 1.128035
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnsig_2 {c |}{col 18}{res}{space 2}-2.198881{col 30}{space 2}  .045626{col 41}{space 1}  -48.19{col 50}{space 3}0.000{col 58}{space 4}-2.288306{col 71}{space 3}-2.109455
{txt}    /atanhrho_12 {c |}{col 18}{res}{space 2}-.0128406{col 30}{space 2} .0316878{col 41}{space 1}   -0.41{col 50}{space 3}0.685{col 58}{space 4}-.0749476{col 71}{space 3} .0492663
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
           sig_2 {c |}{col 18}{res}{space 2} .1109273{col 30}{space 2} .0050612{col 58}{space 4} .1014382{col 71}{space 3}  .121304
{txt}          rho_12 {c |}{col 18}{res}{space 2}-.0128399{col 30}{space 2} .0316826{col 58}{space 4}-.0748076{col 71}{space 3} .0492265
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Warning: convergence not achieved

{com}. 
. estimates store sem1
{txt}
{com}. estimates save sem1, replace
{res}{txt}(note: file sem1.ster not found)
{txt}file sem1.ster saved

{com}. 
. 
. *** Model 6 in Table 2
. 
. gen interaction3=externalef*ideolprime 
{txt}
{com}. 
. label var interaction3 "Pol Efficacy * Ideol proximity"
{txt}
{com}. 
. 
. bootstrap, clu(code study_id) rep(100):   cmp (governmentvote = corruption ideolcor ideolprime  externalef interaction3 $controls $macros) (externalef= corruption  $controls2  $macros2), ind(4 1) nolr qui   iter(100)
{txt}(running cmp on estimation sample)

Bootstrap replications ({res}100{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
..................................................    50
..................................................   100
{res}
{txt}Mixed-process regression{col 49}Number of obs{col 67}= {res}    66,987
{txt}{col 49}Replications{col 67}= {res}       100
{txt}{col 49}Wald chi2({res}27{txt}){col 67}= {res}  11632.18
{txt}Log likelihood = {res} -32925.66{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Replications based on {res:88} clusters in code study_id)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}   Observed{col 30}   Bootstrap{col 58}         Norm{col 71}al-based
{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}governmentvote   {txt}{c |}
{space 6}corruption {c |}{col 18}{res}{space 2}-.5167774{col 30}{space 2} .1854997{col 41}{space 1}   -2.79{col 50}{space 3}0.005{col 58}{space 4}-.8803501{col 71}{space 3}-.1532046
{txt}{space 8}ideolcor {c |}{col 18}{res}{space 2}-.0536483{col 30}{space 2} .0214238{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.0956382{col 71}{space 3}-.0116584
{txt}{space 6}ideolprime {c |}{col 18}{res}{space 2} .0747784{col 30}{space 2} .0138687{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0475964{col 71}{space 3} .1019605
{txt}{space 6}externalef {c |}{col 18}{res}{space 2}-2.926406{col 30}{space 2} .0620056{col 41}{space 1}  -47.20{col 50}{space 3}0.000{col 58}{space 4}-3.047935{col 71}{space 3}-2.804877
{txt}{space 4}interaction3 {c |}{col 18}{res}{space 2} .0317458{col 30}{space 2}  .009332{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0134553{col 71}{space 3} .0500362
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0014039{col 30}{space 2} .0006593{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.0026962{col 71}{space 3}-.0001117
{txt}{space 12}male {c |}{col 18}{res}{space 2}-.0440524{col 30}{space 2} .0118826{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.0673418{col 71}{space 3} -.020763
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0199214{col 30}{space 2} .0063157{col 41}{space 1}    3.15{col 50}{space 3}0.002{col 58}{space 4} .0075429{col 71}{space 3} .0322999
{txt}{space 4}loweducation {c |}{col 18}{res}{space 2} .0411541{col 30}{space 2}  .028328{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0143678{col 71}{space 3} .0966759
{txt}{space 3}higheducation {c |}{col 18}{res}{space 2} .0324079{col 30}{space 2} .0196287{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0060635{col 71}{space 3} .0708794
{txt}{space 6}unemployed {c |}{col 18}{res}{space 2}  -.02609{col 30}{space 2} .0316489{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.0881208{col 71}{space 3} .0359408
{txt}{space 9}retired {c |}{col 18}{res}{space 2} .0794331{col 30}{space 2} .0220432{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0362292{col 71}{space 3} .1226369
{txt}{space 11}other {c |}{col 18}{res}{space 2} .0216486{col 30}{space 2} .0234141{col 41}{space 1}    0.92{col 50}{space 3}0.355{col 58}{space 4}-.0242422{col 71}{space 3} .0675393
{txt}{space 8}partisan {c |}{col 18}{res}{space 2} 1.342531{col 30}{space 2} .0634038{col 41}{space 1}   21.17{col 50}{space 3}0.000{col 58}{space 4} 1.218262{col 71}{space 3} 1.466801
{txt}{space 10}growth {c |}{col 18}{res}{space 2} .0098668{col 30}{space 2} .0071474{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.0041419{col 71}{space 3} .0238755
{txt}{space 13}gdp {c |}{col 18}{res}{space 2} .0051128{col 30}{space 2} .0259628{col 41}{space 1}    0.20{col 50}{space 3}0.844{col 58}{space 4}-.0457734{col 71}{space 3} .0559989
{txt}{space 9}durable {c |}{col 18}{res}{space 2}  .001592{col 30}{space 2} .0012307{col 41}{space 1}    1.29{col 50}{space 3}0.196{col 58}{space 4}-.0008201{col 71}{space 3} .0040041
{txt}{space 8}partyage {c |}{col 18}{res}{space 2}-.0012033{col 30}{space 2} .0014376{col 41}{space 1}   -0.84{col 50}{space 3}0.403{col 58}{space 4}-.0040209{col 71}{space 3} .0016143
{txt}{space 14}pr {c |}{col 18}{res}{space 2} .1613382{col 30}{space 2} .0915764{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0181482{col 71}{space 3} .3408246
{txt}{space 8}pluralty {c |}{col 18}{res}{space 2} .0665236{col 30}{space 2} .0982226{col 41}{space 1}    0.68{col 50}{space 3}0.498{col 58}{space 4}-.1259891{col 71}{space 3} .2590363
{txt}{space 12}mdmh {c |}{col 18}{res}{space 2} .0053872{col 30}{space 2} .0012355{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0029656{col 71}{space 3} .0078087
{txt}{space 9}p_effnv {c |}{col 18}{res}{space 2}-.0641657{col 30}{space 2} .0259948{col 41}{space 1}   -2.47{col 50}{space 3}0.014{col 58}{space 4}-.1151145{col 71}{space 3}-.0132168
{txt}{space 11}p_maj {c |}{col 18}{res}{space 2} .3411873{col 30}{space 2} .3314835{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.3085084{col 71}{space 3}  .990883
{txt}{space 11}state {c |}{col 18}{res}{space 2}  .079608{col 30}{space 2} .1150444{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4}-.1458749{col 71}{space 3} .3050908
{txt}{space 12}east {c |}{col 18}{res}{space 2} .2116002{col 30}{space 2} .1301052{col 41}{space 1}    1.63{col 50}{space 3}0.104{col 58}{space 4}-.0434012{col 71}{space 3} .4666017
{txt}{space 9}noneuro {c |}{col 18}{res}{space 2} -.167836{col 30}{space 2} .0988025{col 41}{space 1}   -1.70{col 50}{space 3}0.089{col 58}{space 4}-.3614854{col 71}{space 3} .0258135
{txt}{space 10}system {c |}{col 18}{res}{space 2}-.2985602{col 30}{space 2} .0868659{col 41}{space 1}   -3.44{col 50}{space 3}0.001{col 58}{space 4}-.4688142{col 71}{space 3}-.1283062
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.578388{col 30}{space 2} .3131382{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .9646488{col 71}{space 3} 2.192128
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}externalef       {txt}{c |}
{space 6}corruption {c |}{col 18}{res}{space 2}-.1974777{col 30}{space 2}  .038135{col 41}{space 1}   -5.18{col 50}{space 3}0.000{col 58}{space 4} -.272221{col 71}{space 3}-.1227345
{txt}{space 13}age {c |}{col 18}{res}{space 2}-.0003654{col 30}{space 2} .0001474{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.0006542{col 71}{space 3}-.0000766
{txt}{space 12}male {c |}{col 18}{res}{space 2} -.006194{col 30}{space 2} .0023748{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.0108486{col 71}{space 3}-.0015394
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0059168{col 30}{space 2} .0011539{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .0036553{col 71}{space 3} .0081783
{txt}{space 4}loweducation {c |}{col 18}{res}{space 2}-.0044229{col 30}{space 2} .0068103{col 41}{space 1}   -0.65{col 50}{space 3}0.516{col 58}{space 4}-.0177708{col 71}{space 3} .0089251
{txt}{space 3}higheducation {c |}{col 18}{res}{space 2} .0175874{col 30}{space 2} .0055627{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .0066848{col 71}{space 3} .0284901
{txt}{space 6}unemployed {c |}{col 18}{res}{space 2}-.0145055{col 30}{space 2} .0074122{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.0290332{col 71}{space 3} .0000221
{txt}{space 9}retired {c |}{col 18}{res}{space 2} .0144077{col 30}{space 2} .0061502{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0023536{col 71}{space 3} .0264618
{txt}{space 11}other {c |}{col 18}{res}{space 2} .0068447{col 30}{space 2} .0060986{col 41}{space 1}    1.12{col 50}{space 3}0.262{col 58}{space 4}-.0051084{col 71}{space 3} .0187977
{txt}strengthpartisan {c |}{col 18}{res}{space 2} .0581789{col 30}{space 2} .0031904{col 41}{space 1}   18.24{col 50}{space 3}0.000{col 58}{space 4} .0519259{col 71}{space 3}  .064432
{txt}{space 13}gdp {c |}{col 18}{res}{space 2}-.0075864{col 30}{space 2} .0062009{col 41}{space 1}   -1.22{col 50}{space 3}0.221{col 58}{space 4}-.0197399{col 71}{space 3} .0045672
{txt}{space 9}durable {c |}{col 18}{res}{space 2} .0003845{col 30}{space 2} .0003061{col 41}{space 1}    1.26{col 50}{space 3}0.209{col 58}{space 4}-.0002155{col 71}{space 3} .0009844
{txt}{space 8}partyage {c |}{col 18}{res}{space 2}-.0003322{col 30}{space 2} .0003164{col 41}{space 1}   -1.05{col 50}{space 3}0.294{col 58}{space 4}-.0009522{col 71}{space 3} .0002879
{txt}{space 14}pr {c |}{col 18}{res}{space 2} .0495479{col 30}{space 2} .0191508{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4}  .012013{col 71}{space 3} .0870827
{txt}{space 8}pluralty {c |}{col 18}{res}{space 2}-.0026815{col 30}{space 2} .0210143{col 41}{space 1}   -0.13{col 50}{space 3}0.898{col 58}{space 4}-.0438688{col 71}{space 3} .0385058
{txt}{space 12}mdmh {c |}{col 18}{res}{space 2} .0014309{col 30}{space 2} .0003662{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0007133{col 71}{space 3} .0021486
{txt}{space 9}p_effnv {c |}{col 18}{res}{space 2}-.0138008{col 30}{space 2} .0061207{col 41}{space 1}   -2.25{col 50}{space 3}0.024{col 58}{space 4}-.0257971{col 71}{space 3}-.0018044
{txt}{space 11}p_maj {c |}{col 18}{res}{space 2} .0203334{col 30}{space 2} .0914738{col 41}{space 1}    0.22{col 50}{space 3}0.824{col 58}{space 4}-.1589519{col 71}{space 3} .1996187
{txt}{space 11}state {c |}{col 18}{res}{space 2} .0196095{col 30}{space 2} .0219684{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4}-.0234478{col 71}{space 3} .0626669
{txt}{space 12}east {c |}{col 18}{res}{space 2} .0824025{col 30}{space 2}  .033591{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0165654{col 71}{space 3} .1482396
{txt}{space 9}noneuro {c |}{col 18}{res}{space 2}-.0424764{col 30}{space 2} .0215786{col 41}{space 1}   -1.97{col 50}{space 3}0.049{col 58}{space 4}-.0847696{col 71}{space 3}-.0001831
{txt}{space 10}system {c |}{col 18}{res}{space 2}-.0782864{col 30}{space 2} .0190759{col 41}{space 1}   -4.10{col 50}{space 3}0.000{col 58}{space 4}-.1156745{col 71}{space 3}-.0408984
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .7611988{col 30}{space 2} .0674121{col 41}{space 1}   11.29{col 50}{space 3}0.000{col 58}{space 4} .6290735{col 71}{space 3} .8933241
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnsig_2 {c |}{col 18}{res}{space 2}-1.254476{col 30}{space 2}  .016263{col 41}{space 1}  -77.14{col 50}{space 3}0.000{col 58}{space 4}-1.286351{col 71}{space 3}-1.222601
{txt}    /atanhrho_12 {c |}{col 18}{res}{space 2} 1.255686{col 30}{space 2} .0545467{col 41}{space 1}   23.02{col 50}{space 3}0.000{col 58}{space 4} 1.148776{col 71}{space 3} 1.362595
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
           sig_2 {c |}{col 18}{res}{space 2} .2852254{col 30}{space 2} .0046386{col 58}{space 4} .2762772{col 71}{space 3} .2944633
{txt}          rho_12 {c |}{col 18}{res}{space 2} .8498703{col 30}{space 2} .0151487{col 58}{space 4} .8173482{col 71}{space 3} .8769936
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store sem2
{txt}
{com}. estimates save sem2, replace
{res}{txt}(note: file sem2.ster not found)
{txt}file sem2.ster saved

{com}. 
. ***Create Table 2 in article and Table 5 in Online Appendix
. 
. esttab simple sem1 sem2  using simmmodels.tex, replace b(3) se(3) scalars(ll) label unstack 
{res}{txt}(output written to {browse  `"simmmodels.tex"'})

{com}. esttab simple sem1 sem2 using simmmodels.tex, replace b(3) se(3) scalars(ll) label unstack keep(corruption ideolcor ideolprime interaction ideoldifference interaction3 externalef)
{res}{txt}(output written to {browse  `"simmmodels.tex"'})

{com}. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\burlacue\Dropbox\Corruption papper\DATAVERSE\probit-models-of-vote-for-the-incumbent.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}19 Oct 2017, 01:06:29
{txt}{.-}
{smcl}
{txt}{sf}{ul off}